Search Results - probable distribution ((means algorithm) OR (bees algorithm))

Determining penetration limit of central distributed generation topology in radial distribution networks by Suliman, Mohamed Saad Abdelgadir

“…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems by Tam, Jun Hui, Ong, Zhi Chao, Ismail, Zubaidah, Ang, Bee Chin, Khoo, Shin Yee

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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…This paper presents an enhanced Artifi cial Bee Colony (eABC) based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm by Shalash, Nadheer A., Abu Zaharin, Ahmad

“…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. …”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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An improvement on the valiantbrebner hypercube data broadcasting technique / Nasaruddin Zenon by Zenon, Nasaruddin

“…The writer tries to improve this algorithm because it is the only known algorithm for the hypercube machine that has the probability of more than i (log n) processors will simultaneously try to transmit a message through a given processor decreases exponentially with i. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…In recent years, photovoltaic distributed generation (PVDG) has seen rapid growth due to its benefits in supporting the power system network, enhancing the transmission and distribution of power, and minimizing power congestion. …”
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Battery management optimization and lifecycle impact analysis for microgrid operation with V2G implementation / Muhammad Sufyan by Muhammad , Sufyan

“…The proposed energy management approach is solved using firefly algorithm, artificial bee colony, harmony search algorithm and particle swarm optimization. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

“…Although the number of these target-like data is small, they may cause false alarm and perturb the target detection. K-distribution is known as the best fit probability density function for the radar sea clutter. …”
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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires by Muhammad Faris Fuaad

A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties by Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir

“…This study proposes a new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping (MVMO-SH) optimisation​ for planning Photovoltaic Distributed Generation (PVDG) in the urban Radial Distribution Network (RDN). …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

“…The first agent employed fuzzy parameters such as, current with its means and variances and the second agent is the probability of outage capacity for each state. …”
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Malay continuous speech recognition using continuous density hidden Markov model by Ting, Chee Ming

“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong by Karoon, Suksonghong

“…The superiority of this method is its ability to generate a set of MVS efficient portfolios within a single run of algorithm. The non-dominated sorting genetic algorithm II (NSGA-II), the improved strength Pareto evolutionary algorithm II (SPEA-II), and the compressed objective genetic algorithm II (COGA-II) were applied. …”
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Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

“…The TESI retained the features’ original probability distribution in the four datasets. The C-TESI achieved the lowest mean squared error mean percentage (MAEP) on the oil palm (0.60–2.85%), rice (0.77–1.72%), and fertiliser datasets (2.04–2.21%). …”
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Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting by YAXING, WEI, HUZAIFA, HASHIM, Lai, Sai Hin, CHONG, KAI LUN, HUANG, YUK FENG, ALI NAJAH, AHMED, MOHSEN, SHERIF, AHMED, EL-SHAFIE

“…Using Bayesian neural networks, we modeled network weights and biases as probability distributions to assess aleatoric and epistemic variability, employing Markov chain Monte Carlo and bootstrap resampling techniques. …”
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